IVGCVSW-8275 GpuFsa Op: Add Activation functions available
* Currently Sigmoid and TanH Functions are implemented.
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: If9483be9201dfe47b86acc41ec7932725ac2e39e
diff --git a/src/backends/gpuFsa/layers/GpuFsaActivation.cpp b/src/backends/gpuFsa/layers/GpuFsaActivation.cpp
new file mode 100644
index 0000000..4b0773f
--- /dev/null
+++ b/src/backends/gpuFsa/layers/GpuFsaActivation.cpp
@@ -0,0 +1,126 @@
+//
+// Copyright © 2024 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "GpuFsaActivation.hpp"
+
+#include <aclCommon/ArmComputeTensorUtils.hpp>
+
+#include <arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadContext.h>
+#include <arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h>
+#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuTanh.h>
+#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuSigmoid.h>
+#include <arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h>
+
+using namespace arm_compute::experimental::dynamic_fusion;
+using namespace armnn::armcomputetensorutils;
+
+namespace armnn
+{
+
+arm_compute::Status GpuFsaActivationValidate(const TensorInfo& input,
+ const ActivationDescriptor& descriptor)
+{
+ // Create a new workload sketch, for validation purposes
+ auto compileCtx = arm_compute::CLKernelLibrary::get().get_compile_context();
+ auto workloadContext = GpuWorkloadContext(&compileCtx);
+ GpuWorkloadSketch sketch{ &workloadContext };
+
+ arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, input.GetNumDimensions());
+ aclInputInfo.set_are_values_constant(input.IsConstant());
+
+ arm_compute::ITensorInfo* inputInfo = workloadContext.create_tensor_info(aclInputInfo);
+
+ switch (descriptor.m_Function)
+ {
+ case ActivationFunction::TanH:
+ {
+ if ( descriptor.m_A != 1 || descriptor.m_B != 1)
+ {
+ return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR,
+ "Activation function TanH only works with a=1 and b=1");
+ }
+ return GpuTanh::validate_op(sketch, inputInfo);
+ }
+ case ActivationFunction::Sigmoid:
+ {
+ return GpuSigmoid::validate_op(sketch, inputInfo);
+ }
+ default:
+ return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR,
+ std::string("Activation function currently not supported in GpuFsa: ")
+ + GetActivationFunctionAsCString(descriptor.m_Function));
+ }
+
+}
+
+void GpuFsaActivationCreateOp(GpuFsaPreCompiledBlob* blob,
+ const TensorInfo& input,
+ const ActivationDescriptor& descriptor)
+{
+ GpuWorkloadSketch* sketch = blob->sketch.get();
+ GpuWorkloadContext* workloadContext = blob->workloadContext.get();
+ std::vector<arm_compute::ITensorInfo*> inputTensorInfos = {};
+ std::vector<arm_compute::ITensorInfo*> outputTensorInfos = {};
+
+ arm_compute::TensorInfo aclInput0Info = BuildArmComputeTensorInfo(input, input.GetNumDimensions());
+
+ aclInput0Info.set_are_values_constant(input.IsConstant());
+
+ inputTensorInfos.emplace_back(workloadContext->create_tensor_info(aclInput0Info));
+
+ // Validate operator, check status and update reasonIfUnsupported
+ arm_compute::Status aclStatus{};
+ switch (descriptor.m_Function)
+ {
+ case ActivationFunction::TanH:
+ {
+ aclStatus = GpuTanh::validate_op(*sketch, inputTensorInfos[0]);
+ break;
+ }
+ case ActivationFunction::Sigmoid:
+ {
+ aclStatus = GpuSigmoid::validate_op(*sketch, inputTensorInfos[0]);
+ break;
+ }
+ default:
+ throw InvalidArgumentException(std::string("Activation function currently not supported in GpuFsa: ")
+ + GetActivationFunctionAsCString(descriptor.m_Function));
+
+ }
+ const bool supported = aclStatus.error_code() == arm_compute::ErrorCode::OK;
+ if (!supported)
+ {
+ throw BackendCapabilityException("\"GpuFsa\" backend failed during Activation layer validation");
+ }
+
+ arm_compute::ITensorInfo* activationOutputInfo{};
+ switch (descriptor.m_Function)
+ {
+ case ActivationFunction::TanH:
+ {
+ activationOutputInfo = GpuTanh::create_op(*sketch, inputTensorInfos[0]);
+ break;
+ }
+ case ActivationFunction::Sigmoid:
+ {
+ activationOutputInfo = GpuSigmoid::create_op(*sketch, inputTensorInfos[0]);
+ break;
+ }
+ default:
+ throw InvalidArgumentException(std::string("Activation function currently not supported in GpuFsa: ")
+ + GetActivationFunctionAsCString(descriptor.m_Function));
+
+ }
+
+ // Temporary fix until fusing attempt is make for GpuFsa backend and Output layer workload is created.
+ outputTensorInfos.emplace_back(workloadContext->create_tensor_info());
+ GpuOutput::create_op(*sketch, activationOutputInfo, outputTensorInfos[0]);
+
+ // Store the TensorInfos within the blob as unique_ptrs to be used later
+ blob->inputTensorInfos = std::make_unique<std::vector<arm_compute::ITensorInfo*>>(inputTensorInfos);
+ blob->outputTensorInfos = std::make_unique<std::vector<arm_compute::ITensorInfo*>>(outputTensorInfos);
+}
+
+} // namespace armnn
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